About DataTrails

DataTrails offers a Provenance API that generates immutable audit trails for digital content, ensuring verifiable authenticity and data lineage. This technology addresses the need for transparency in multi-party scenarios, enabling organizations to maintain trust and compliance in their data distribution processes.

```xml <problem> In the age of AI-generated content and widespread data sharing, organizations struggle to maintain transparency and trust in their digital assets. Verifying the authenticity and tracking the lineage of data across multiple parties is challenging, leading to concerns about compliance, fraud, and misattribution. </problem> <solution> DataTrails provides a Provenance API that generates immutable audit trails for digital content, ensuring verifiable authenticity and data lineage. The API associates the identity of operations with the actions and events of a workflow, creating a tamper-proof record of who did what and when. By linking content with immutable metadata and cryptographic hashes, DataTrails enables users to instantly verify content and determine if assets are trusted. The platform supports IETF SCITT standards, facilitating integration with applications that require safe, secure, and trustworthy data. </solution> <features> - Provenance API for generating immutable audit trails - Cryptographic hashing and metadata linking for content verification - Support for IETF SCITT standards for interoperability - Tamper-proof ledger for recording chronological sequences of activities - Tools for identifying training datasets used in AI models - Features for tracking outputs with verifiability and transparency - Integration capabilities for chain of custody solutions - Proof Portal for durable media protection to verify content authenticity and debunk deepfakes </features> <target_audience> DataTrails targets tech teams building responsible AI, media teams focused on content authenticity, and supply chain teams seeking enhanced oversight. </target_audience> ```

What does DataTrails do?

Where is DataTrails located?

DataTrails is based in Santa Clara, Cuba.

When was DataTrails founded?

DataTrails was founded in 2018.

How much funding has DataTrails raised?

DataTrails has raised $12.7M.

Location

Santa Clara, Cuba

Founded

2018

Funding

$12.7M

Investors

Ridgeline

DataTrails

Santa Clara, CubaFounded 20183/10 TractionRelative Traction Score based on online presence metrics compared to companies in the same age group.

Updated 3 months ago

Funding

$12.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

In the age of AI-generated content and widespread data sharing, organizations struggle to maintain transparency and trust in their digital assets. Verifying the authenticity and tracking the lineage of data across multiple parties is challenging, leading to concerns about compliance, fraud, and misattribution.

Solution

DataTrails provides a Provenance API that generates immutable audit trails for digital content, ensuring verifiable authenticity and data lineage. The API associates the identity of operations with the actions and events of a workflow, creating a tamper-proof record of who did what and when. By linking content with immutable metadata and cryptographic hashes, DataTrails enables users to instantly verify content and determine if assets are trusted. The platform supports IETF SCITT standards, facilitating integration with applications that require safe, secure, and trustworthy data.

Target Audience

DataTrails targets tech teams building responsible AI, media teams focused on content authenticity, and supply chain teams seeking enhanced oversight.

Features

Provenance API for generating immutable audit trails
Cryptographic hashing and metadata linking for content verification
Support for IETF SCITT standards for interoperability
Tamper-proof ledger for recording chronological sequences of activities
Tools for identifying training datasets used in AI models
Features for tracking outputs with verifiability and transparency
Integration capabilities for chain of custody solutions
Proof Portal for durable media protection to verify content authenticity and debunk deepfakes